Musings of an Amateur Mythographer I: Islands of Certainty in a Sea of Confusion
Posted: June 23, 2015 Filed under: Education, Opinion | Tags: advocacy, authenticity, blogging, Claude Lévi-Strauss, design, education, educational problem, educational research, evidence, higher education, Karl Popper, Lévi-Strauss, learning, moocs, myth, mythographer, reflection, resources, scientific thinking, teaching, teaching approaches, thinking, tools Leave a commentI’ve been doing a lot of reading recently on the classification of knowledge, the development of scientific thinking, the ways different cultures approach learning, and the relationship between myths and science. Now, some of you are probably wondering why I can’t watch “Agents of S.H.I.E.L.D.” like a normal person but others of you have already started to shift uneasily because I’ve talked about a relationship between myths and science, as if we do not consider science to be the natural successor to preceding myths. Well, let me go further. I’m about to start drawing on thinking on myths and science and even how the myths that teach us about the importance of evidence, the foundation of science, but for their own purposes.
Why?
Because much of what we face as opposition in educational research are pre-existing stereotypes and misconceptions that people employ, where there’s a lack of (and sometimes in the face of) evidence. Yet this collection of beliefs is powerful because it prevents people from adopting verified and validated approaches to learning and teaching. What can we call these? Are these myths? What do I even mean by that term?
It’s important to realise that the use of the term myth has evolved from earlier, rather condescending, classifications of any culture’s pre-scientific thinking as being dismissively primitive and unworthy of contemporary thought. This is a rich topic by itself but let me refer to Claude Lévi-Strauss and his identification of myth as being a form of thinking and classification, rather than simple story-telling, and thus proto-scientific, rather than anti-scientific. I note that I have done the study of mythology a grave disservice with such an abbreviated telling. Further reading here to understand precisely what Lévi-Strauss was refuting could involve Tylor, Malinowski, and Lévy-Bruhl. This includes rejecting a knee-jerk classification of a less scientifically advanced people as being emotional and practical, rather than (even being capable of) being intellectual. By moving myth forms to an intellectual footing, Lévi-Strauss allows a non-pejorative assessment of the potential value of myth forms.
In many situations, we consider myth and folklore as the same thing, from a Western post-Enlightenment viewpoint, only accepting those elements that we can validate. Thus, we choose not to believe that Olympus holds the Greek Pantheon as we cannot locate the Gods reliably, but the pre-scientific chewing of willow bark to relieve pain was validated once we constructed aspirin (and willow bark tea). It’s worth noting that the early location of willow bark as part of its scientific ‘discovery’ was inspired by an (effectively random) approach called the doctrine of signatures, which assumed that the cause and the cure of diseases would be located near each other. The folkloric doctrine of signatures led the explorers to a plant that tasted like another one but had a different use.
Myth, folklore and science, dancing uneasily together. Does this mean that what we choose to call myth now may or may not be myth in the future? We know that when to use it, to recommend it, in our endorsed and academic context is usually to require it to become science. But what is science?
Karl Popper’s (heavily summarised) view is that we have a set of hypotheses that we test to destruction and this is the foundation of our contemporary view of science. If the evidence we have doesn’t fit the hypothesis then we must reject the hypothesis. When we have enough evidence, and enough hypotheses, we have a supported theory. However, this has a natural knock-on effect in that we cannot actually prove anything, we just have enough evidence to support the hypothesis. Kuhn (again, heavily summarised) has a model of “normal science” where there is a large amount of science as in Popper’s model, incrementing a body of existing work, but there are times when this continuity gives way to a revolutionary change. At these times, we see an accumulation of contradictory evidence that illustrates that it’s time to think very differently about the world. Ultimately, we discover the need for a new coherency, where we need new exemplars to make the world make sense. (And, yes, there’s still a lot of controversy over this.)
Let me attempt to bring this all together, finally. We, as humans, live in a world full of information and some of it, even in our post-scientific world, we incorporate into our lives without evidence and some we need evidence to accept. Do you want some evidence that we live our lives without, or even in spite of, evidence? The median length for a marriage in the United States is 11 years and 40-50% of marriages will end in divorce yet many still swear ‘until death do us part’ or ‘all of my days’. But the myth of ‘marriage forever’ is still powerful. People have children, move, buy houses and totally change their lives based on this myth. The actions that people take here will have a significant impact on the world around them and yet it seems at odd with the evidence. (Such examples are not uncommon and, in a post-scientific revolution world, must force us to consider earlier suggestions that myth-based societies move seamlessly to a science-based intellectual utopia. This is why Lévi-Strauss is interesting to read. Our evidence is that our evidence is not sufficient evidence, so we must seek to better understand ourselves.) Even those components of our shared history and knowledge that are constructed to be based on faith, such as religion, understand how important evidence is to us. Let me give an example.
In the fourth book of the New Testament of the Christian Bible, the Gospel of John, we find the story of the Resurrection of Lazarus. Lazarus is sick and Jesus Christ waits until he dies to go to where he is buried and raise him. Jesus deliberately delays because the glory to the Christian God will be far greater and more will believe, if Lazarus is raised from the dead, rather than just healed from illness. Ultimately, and I do not speak for any religious figure or God here, anyone can get better from an illness but to be raised from the dead (currently) requires a miracle. Evidence, even in a book written for the faithful and to build faith, is important to humans.
We also know that there is a very large amount of knowledge that is accepted as being supported by evidence but the evidence is really anecdotal, based on bias and stereotype, and can even be distorted through repetition. This is the sea of confusion that we all live in. The scientific method (Popper) is one way that we can try to find firm ground to stand on but, if Kuhn is to be believed, there is the risk that one day we stand on the islands and realise that the truth was the sea all along. Even with Popper, we risk standing on solid ground that turns out to be meringue. How many of these changes can one human endure and still be malleable and welcoming in the face of further change?
Our problem with myth is when it forces us to reject something that we can demonstrate to be both valuable and scientifically valid because, right now, the world that we live in is constructed on scientific foundations and coherence is maintained by adding to those foundations. Personally, I don’t believe that myth and science have to be at odds (many disagree with me, including Richard Dawkins of course), and that this is an acceptable view as they are already co-existing in ways that actively shape society, for both good and ill.
Recently I made a comment on MOOCs that contradicted something someone said and I was (quite rightly) asked to provide evidence to support my assertions. That is the post before this one and what you will notice is that I do not have a great deal of what we would usually call evidence: no double-blind tests, no large-n trials with well-formed datasets. I had some early evidence of benefit, mostly qualitative and relatively soft, but, and this is important to me, what I didn’t have was evidence of harm. There are many myths around MOOCs and education in general. Some of them fall into the realm of harmful myths, those that cause people to reject good approaches to adhere to old and destructive practices. Some of them are harmful because they cause us to reject approaches that might work because we cannot find the evidence we need.
I am unsurprised that so many people adhere to folk pedagogy, given the vast amounts of information out there and the natural resistance to rejecting something that you think works, especially when someone sails in and tells you’ve been wrong for years. The fact that we are still discussing the nature of myth and science gives insight into how complicated this issue is.
I think that the path I’m on could most reasonably be called that of the mythographer, but the cataloguing of the edges of myth and the intersections of science is not in order to condemn one or the other but to find out what the truth is to the best of our knowledge. I think that understanding why people believe what they believe allows us to understand what they will need in order to believe something that is actually, well, true. There are many articles written on this, on the difficulty of replacing one piece of learning with another and the dangers of repetition in reinforcing previously-held beliefs, but there is hope in that we can construct new elements to replace old information if we are careful and we understand how people think.
We need to understand the delicate relationships between myth, folklore and science, our history as separate and joined peoples, if only to understand when we have achieved new forms of knowing. But we also need to be more upfront about when we believe we have moved on, including actively identifying areas that we have labelled as “in need of much more evidence” (such as learning styles, for example) to assist people in doing valuable work if they wish to pursue research.
I’ll go further. If we have areas where we cannot easily gain evidence, yet we have competing myths in that space, what should we do? How do we choose the best approach to achieve the most effective educational outcomes? I’ll let everyone argue in the comments for a while and then write that as the next piece.
Designing a MOOC: how far did it reach? #csed
Posted: June 10, 2015 Filed under: Education, Opinion | Tags: advocacy, authenticity, blogging, collaboration, community, computer science education, constructivist, contributing student pedagogy, curriculum, data visualisation, design, education, educational problem, educational research, ethics, feedback, higher education, in the student's head, learning, measurement, MOOC, moocs, principles of design, reflection, resources, students, teaching, teaching approaches, thinking, tools Leave a commentMark Guzdial posted over on his blog on “Moving Beyond MOOCS: Could we move to understanding learning and teaching?” and discusses aspects (that still linger) of MOOC hype. (I’ve spoken about MOOCs done badly before, as well as recording the thoughts of people like Hugh Davis from Southampton.) One of Mark’s paragraphs reads:
“The value of being in the front row of a class is that you talk with the teacher. Getting physically closer to the lecturer doesn’t improve learning. Engagement improves learning. A MOOC puts everyone at the back of the class, listening only and doing the homework”
My reply to this was:
“You can probably guess that I have two responses here, the first is that the front row is not available to many in the real world in the first place, with the second being that, for far too many people, any seat in the classroom is better than none.
But I am involved in a, for us, large MOOC so my responses have to be regarded in that light. Thanks for the post!”
Mark, of course, called my bluff and responded with:
“Nick, I know that you know the literature in this space, and care about design and assessment. Can you say something about how you designed your MOOC to reach those who would not otherwise get access to formal educational opportunities? And since your MOOC has started, do you know yet if you achieved that goal — are you reaching people who would not otherwise get access?”
So here is that response. Thanks for the nudge, Mark! The answer is a bit long but please bear with me. We will be posting a longer summary after the course is completed, in a month or so. Consider this the unedited taster. I’m putting this here, early, prior to the detailed statistical work, so you can see where we are. All the numbers below are fresh off the system, to drive discussion and answering Mark’s question at, pretty much, a conceptual level.
First up, as some background for everyone, the MOOC team I’m working with is the University of Adelaide‘s Computer Science Education Research group, led by A/Prof Katrina Falkner, with me (Dr Nick Falkner), Dr Rebecca Vivian, and Dr Claudia Szabo.
I’ll start by noting that we’ve been working to solve the inherent scaling issues in the front of the classroom for some time. If I had a class of 12 then there’s no problem in engaging with everyone but I keep finding myself in rooms of 100+, which forces some people to sit away from me and also limits the number of meaningful interactions I can make to individuals in one setting. While I take Mark’s point about the front of the classroom, and the associated research is pretty solid on this, we encountered an inherent problem when we identified that students were better off down the front… and yet we kept teaching to rooms with more student than front. I’ll go out on a limb and say that this is actually a moral issue that we, as a sector, have had to look at and ignore in the face of constrained resources. The nature of large spaces and people, coupled with our inability to hover, means that we can either choose to have a row of students effectively in a semi-circle facing us, or we accept that after a relatively small number of students or number of rows, we have constructed a space that is inherently divided by privilege and will lead to disengagement.
So, Katrina’s and my first foray into this space was dealing with the problem in the physical lecture spaces that we had, with the 100+ classes that we had.
Katrina and I published a paper on “contributing student pedagogy” in Computer Science Education 22 (4), 2012, to identify ways for forming valued small collaboration groups as a way to promote engagement and drive skill development. Ultimately, by reducing the class to a smaller number of clusters and making those clusters pedagogically useful, I can then bring the ‘front of the class’-like experience to every group I speak to. We have given talks and applied sessions on this, including a special session at SIGCSE, because we think it’s a useful technique that reduces the amount of ‘front privilege’ while extending the amount of ‘front benefit’. (Read the paper for actual detail – I am skimping on summary here.)
We then got involved in the support of the national Digital Technologies curriculum for primary and middle school teachers across Australia, after being invited to produce a support MOOC (really a SPOC, small, private, on-line course) by Google. The target learners were teachers who were about to teach or who were teaching into, initially, Foundation to Year 6 and thus had degrees but potentially no experience in this area. (I’ve written about this before and you can find more detail on this here, where I also thanked my previous teachers!)
The motivation of this group of learners was different from a traditional MOOC because (a) everyone had both a degree and probable employment in the sector which reduced opportunistic registration to a large extent and (b) Australian teachers are required to have a certain number of professional development (PD) hours a year. Through a number of discussions across the key groups, we had our course recognised as PD and this meant that doing our course was considered to be valuable although almost all of the teachers we spoke to were furiously keen for this information anyway and my belief is that the PD was very much ‘icing’ rather than ‘cake’. (Thank you again to all of the teachers who have spent time taking our course – we really hope it’s been useful.)
To discuss access and reach, we can measure teachers who’ve taken the course (somewhere in the low thousands) and then estimate the number of students potentially assisted and that’s when it gets a little crazy, because that’s somewhere around 30-40,000.
In his talk at CSEDU 2014, Hugh Davis identified the student groups who get involved in MOOCs as follows. The majority of people undertaking MOOCs were life-long learners (older, degreed, M/F 50/50), people seeking skills via PD, and those with poor access to Higher Ed. There is also a small group who are Uni ‘tasters’ but very, very small. (I think we can agree that tasting a MOOC is not tasting a campus-based Uni experience. Less ivy, for starters.) The three approaches to the course once inside were auditing, completing and sampling, and it’s this final one that I want to emphasise because this brings us to one of the differences of MOOCs. We are not in control of when people decide that they are satisfied with the free education that they are accessing, unlike our strong gatekeeping on traditional courses.
I am in total agreement that a MOOC is not the same as a classroom but, also, that it is not the same as a traditional course, where we define how the student will achieve their goals and how they will know when they have completed. MOOCs function far more like many people’s experience of web browsing: they hunt for what they want and stop when they have it, thus the sampling engagement pattern above.
(As an aside, does this mean that a course that is perceived as ‘all back of class’ will rapidly be abandoned because it is distasteful? This makes the student-consumer a much more powerful player in their own educational market and is potentially worth remembering.)
Knowing these different approaches, we designed the individual subjects and overall program so that it was very much up to the participant how much they chose to take and individual modules were designed to be relatively self-contained, while fitting into a well-designed overall flow that built in terms of complexity and towards more abstract concepts. Thus, we supported auditing, completing and sampling, whereas our usual face-to-face (f2f) courses only support the first two in a way that we can measure.
As Hugh notes, and we agree through growing experience, marking/progress measures at scale are very difficult, especially when automated marking is not enough or not feasible. Based on our earlier work in contributing collaboration in the class room, for the F-6 Teacher MOOC we used a strong peer-assessment model where contributions and discussions were heavily linked. Because of the nature of the cohort, geographical and year-level groups formed who then conducted additional sessions and produced shared material at a slightly terrifying rate. We took the approach that we were not telling teachers how to teach but we were helping them to develop and share materials that would assist in their teaching. This reduced potential divisions and allows us to establish a mutually respectful relationship that facilitated openness.
(It’s worth noting that the courseware is creative commons, open and free. There are people reassembling the course for their specific take on the school system as we speak. We have a national curriculum but a state-focused approach to education, with public and many independent systems. Nobody makes any money out of providing this course to teachers and the material will always be free. Thank you again to Google for their ongoing support and funding!)
Overall, in this first F-6 MOOC, we had higher than usual retention of students and higher than usual participation, for the reasons I’ve outlined above. But this material was for curriculum support for teachers of young students, all of whom were pre-programming, and it could be contained in videos and on-line sharing of materials and discussion. We were also in the MOOC sweet-spot: existing degreed learners, PD driver, and their PD requirement depended on progressive demonstration on goal achievement, which we recognised post-course with a pre-approved certificate form. (Important note: if you are doing this, clear up how the PD requirements are met and how they need to be reported back, as early on as you can. It meant that we could give people something valuable in a short time.)
The programming MOOC, Think. Create. Code on EdX, was more challenging in many regards. We knew we were in a more difficult space and would be more in what I shall refer to as ‘the land of the average MOOC consumer’. No strong focus, no PD driver, no geographically guaranteed communities. We had to think carefully about what we considered to be useful interaction with the course material. What counted as success?
To start with, we took an image-based approach (I don’t think I need to provide supporting arguments for media-driven computing!) where students would produce images and, over time, refine their coding skills to produce and understand how to produce more complex images, building towards animation. People who have not had good access to education may not understand why we would use programming in more complex systems but our goal was to make images and that is a fairly universally understood idea, with a short production timeline and very clear indication of achievement: “Does it look like a face yet?”
In terms of useful interaction, if someone wrote a single program that drew a face, for the first time – then that’s valuable. If someone looked at someone else’s code and spotted a bug (however we wish to frame this), then that’s valuable. I think that someone writing a single line of correct code, where they understand everything that they write, is something that we can all consider to be valuable. Will it get you a degree? No. Will it be useful to you in later life? Well… maybe? (I would say ‘yes’ but that is a fervent hope rather than a fact.)
So our design brief was that it should be very easy to get into programming immediately, with an active and engaged approach, and that we have the same “mostly self-contained week” approach, with lots of good peer interaction and mutual evaluation to identify areas that needed work to allow us to build our knowledge together. (You know I may as well have ‘social constructivist’ tattooed on my head so this is strongly in keeping with my principles.) We wrote all of the materials from scratch, based on a 6-week program that we debated for some time. Materials consisted of short videos, additional material as short notes, participatory activities, quizzes and (we planned for) peer assessment (more on that later). You didn’t have to have been exposed to “the lecture” or even the advanced classroom to take the course. Any exposure to short videos or a web browser would be enough familiarity to go on with.
Our goal was to encourage as much engagement as possible, taking into account the fact that any number of students over 1,000 would be very hard to support individually, even with the 5-6 staff we had to help out. But we wanted students to be able to develop quickly, share quickly and, ultimately, comment back on each other’s work quickly. From a cognitive load perspective, it was crucial to keep the number of things that weren’t relevant to the task to a minimum, as we couldn’t assume any prior familiarity. This meant no installers, no linking, no loaders, no shenanigans. Write program, press play, get picture, share to gallery, winning.
As part of this, our support team (thanks, Jill!) developed a browser-based environment for Processing.js that integrated with a course gallery. Students could save their own work easily and share it trivially. Our early indications show that a lot of students jumped in and tried to do something straight away. (Processing is really good for getting something up, fast, as we know.) We spent a lot of time testing browsers, testing software, and writing code. All of the recorded materials used that development environment (this was important as Processing.js and Processing have some differences) and all of our videos show the environment in action. Again, as little extra cognitive load as possible – no implicit requirement for abstraction or skills transfer. (The AdelaideX team worked so hard to get us over the line – I think we may have eaten some of their brains to save those of our students. Thank you again to the University for selecting us and to Katy and the amazing team.)
The actual student group, about 20,000 people over 176 countries, did not have the “built-in” motivation of the previous group although they would all have their own levels of motivation. We used ‘meet and greet’ activities to drive some group formation (which worked to a degree) and we also had a very high level of staff monitoring of key question areas (which was noted by participants as being very high for EdX courses they’d taken), everyone putting in 30-60 minutes a day on rotation. But, as noted before, the biggest trick to getting everyone engaged at the large scale is to get everyone into groups where they have someone to talk to. This was supposed to be provided by a peer evaluation system that was initially part of the assessment package.
Sadly, the peer assessment system didn’t work as we wanted it to and we were worried that it would form a disincentive, rather than a supporting community, so we switched to a forum-based discussion of the works on the EdX discussion forum. At this point, a lack of integration between our own UoA programming system and gallery and the EdX discussion system allowed too much distance – the close binding we had in the R-6 MOOC wasn’t there. We’re still working on this because everything we know and all evidence we’ve collected before tells us that this is a vital part of the puzzle.
In terms of visible output, the amount of novel and amazing art work that has been generated has blown us all away. The degree of difference is huge: armed with approximately 5 statements, the number of different pieces you can produce is surprisingly large. Add in control statements and reputation? BOOM. Every student can write something that speaks to her or him and show it to other people, encouraging creativity and facilitating engagement.
From the stats side, I don’t have access to the raw stats, so it’s hard for me to give you a statistically sound answer as to who we have or have not reached. This is one of the things with working with a pre-existing platform and, yes, it bugs me a little because I can’t plot this against that unless someone has built it into the platform. But I think I can tell you some things.
I can tell you that roughly 2,000 students attempted quiz problems in the first week of the course and that over 4,000 watched a video in the first week – no real surprises, registrations are an indicator of interest, not a commitment. During that time, 7,000 students were active in the course in some way – including just writing code, discussing it and having fun in the gallery environment. (As it happens, we appear to be plateauing at about 3,000 active students but time will tell. We have a lot of post-course analysis to do.)
It’s a mistake to focus on the “drop” rates because the MOOC model is different. We have no idea if the people who left got what they wanted or not, or why they didn’t do anything. We may never know but we’ll dig into that later.
I can also tell you that only 57% of the students currently enrolled have declared themselves explicitly to be male and that is the most likely indicator that we are reaching students who might not usually be in a programming course, because that 43% of others, of whom 33% have self-identified as women, is far higher than we ever see in classes locally. If you want evidence of reach then it begins here, as part of the provision of an environment that is, apparently, more welcoming to ‘non-men’.
We have had a number of student comments that reflect positive reach and, while these are not statistically significant, I think that this also gives you support for the idea of additional reach. Students have been asking how they can save their code beyond the course and this is a good indicator: ownership and a desire to preserve something valuable.
For student comments, however, this is my favourite.
I’m no artist. I’m no computer programmer. But with this class, I see I can be both. #processingjs (Link to student’s work) #code101x .
That’s someone for whom this course had them in the right place in the classroom. After all of this is done, we’ll go looking to see how many more we can find.
I know this is long but I hope it answered your questions. We’re looking forward to doing a detailed write-up of everything after the course closes and we can look at everything.
EduTech AU 2015, Day 2, Higher Ed Leaders, “Change and innovation in the Digital Age: the future is social, mobile and personalised.” #edutechau @timbuckteeth
Posted: June 3, 2015 Filed under: Education | Tags: advocacy, community, curriculum, design, education, educational problem, edutech2015, feedback, Generation Why, higher education, in the student's head, learning, Mayflower, Mayflower steps, measurement, Plymouth University, principles of design, reflection, resources, steve wheeler, student perspective, students, teaching, teaching approaches, technology, thinking, tools Leave a commentAnd heeere’s Steve Wheeler (@timbuckteeth)! Steve is an A/Prof of Learning Technologies at Plymouth in the UK. He and I have been at the same event before (CSEDU, Barcelona) and we seem to agree on a lot. Today’s cognitive bias warning is that I will probably agree with Steve a lot, again. I’ve already quizzed him on his talk because it looked like he was about to try and, as I understand it, what he wants to talk about is how our students can have altered expectations without necessarily becoming some sort of different species. (There are no Digital Natives. No, Prensky was wrong. Check out Helsper, 2010, from the LSE.) So, on to the talk and enough of my nonsense!
Steve claims he’s going to recap the previous speaker, but in an English accent. Ah, the Mayflower steps on the quayside in Plymouth, except that they’re not, because the real Mayflower steps are in a ladies’ loo in a pub, 100m back from the quay. The moral? What you expect to be getting is not always what you get. (Tourists think they have the real thing, locals know the truth.)
“Any sufficiently advanced technology is indistinguishable from magic” – Arthur C. Clarke.
Educational institutions are riddled with bad technology purchases where we buy something, don’t understand it, don’t support it and yet we’re stuck with it or, worse, try to teach with it when it doesn’t work.
Predicting the future is hard but, for educators, we can do it better if we look at:
- Pedagogy first
- Technology next (that fits the technology)
Steve then plugs his own book with a quote on technology not being a silver bullet.
But who will be our students? What are their expectations for the future? Common answers include: collaboration (student and staff), and more making and doing. They don’t like being talked at. Students today do not have a clear memory of the previous century, their expectations are based on the world that they are living in now, not the world that we grew up in.
Meet Student 2.0!
The average digital birth of children happens at about six months – but they can be on the Internet before they are born, via ultrasound photos. (Anyone who has tried to swipe or pinch-zoom a magazine knows why kids take to it so easily.) Students of today have tools and technology and this is what allows them to create, mash up, and reinvent materials.
What about Game Based Learning? What do children learn from playing games
Three biggest fears of teachers using technology
- How do I make this work?
- How do I avoid looking like an idiot?
- They will know more about it than I do.
Three biggest fears of students
- Bad wifi
- Spinning wheel of death
- Low battery
The laptops and devices you see in lectures are personal windows on the world, ongoing conversations and learning activities – it’s not purely inattention or anti-learning. Student questions on Twitter can be answered by people all around the world and that’s extending the learning dialogue out a long way beyond the classroom.
Voltaire said that we were products of our age. Walrick asks how we can prepare students for a future? Steve showed us a picture of him as a young boy, who had been turned off asking questions by a mocking teacher. But the last two years of his schooling were in Holland he went to the Philips flying saucer, which was a technology museum. There, he saw an early video conferencing system and that inspired him with a vision of the future.
Steve wanted to be an astronaut but his career advisor suggested he aim lower, because he wasn’t an American. The point is not that Steve wanted to be an astronaut but that he wanted to be an explorer, the role that he occupies now in education.
Steve shared a quote that education is “about teaching students not subjects” and he shared the awesome picture of ‘named quadrilaterals’. My favourite is ‘Bob. We have a very definite idea of what we want students to write as answer but we suppress creative answers and we don’t necessarily drive the approach to learning that we want.
Ignorance spreads happily by itself, we shouldn’t be helping it. Our visions of the future are too often our memories of what our time was, transferred into modern systems. Our solution spaces are restricted by our fixations on a specific way of thinking. This prevents us from breaking out of our current mindset and doing something useful.
What will the future be? It was multi-media, it was web, but where is it going? Mobile devices because the most likely web browser platform in 2013 and their share is growing.
What will our new technologies be? Thinks get smaller, faster, lighter as they mature. We have to think about solving problems in new ways.
Here’s a fire hose sip of technologies: artificial intelligence is on the way up, touch surfaces are getting better, wearables are getting smarter, we’re looking at remote presence, immersive environments, 3D printers are changing manufacturing and teaching, gestural computing, mind control of devices, actual physical implants into the body…
From Nova Spivak, we can plot information connectivity against social connectivity and we want is growth on both axes – a giant arrow point up to the top right. We don’t yet have a Web form that connects information, knowledge and people – i.e. linking intelligence and people. We’re already seeing some of this with recommenders, intelligent filtering, and sentiment tracking. (I’m still waiting for the Semantic Web to deliver, I started doing work on it in my PhD, mumble years ago.)
A possible topology is: infrastructure is distributed and virtualised, our interfaces are 3D and interactive, built onto mobile technology and using ‘intelligent’ systems underneath.
But you cannot assume that your students are all at the same level or have all of the same devices: the digital divide is as real and as damaging as any social divide. Steve alluded to the Personal Learning Networking, which you can read about in my previous blog on him.
How will teaching change? It has to move away from cutting down students into cloned templates. We want students to be self-directed, self-starting, equipped to capture information, collaborative, and oriented towards producing their own things.
Let’s get back to our roots:
- We learn by doing (Piaget, 1950)
- We learn by making (Papert, 1960)
Just because technology is making some of this doing and making easier doesn’t mean we’re making it worthless, it means that we have time to do other things. Flip the roles, not just the classroom. Let students’ be the teacher – we do learn by teaching. (Couldn’t agree more.)
Back to Papert, “The best learning takes place when students take control.” Students can reflect in blogging as they present their information a hidden audience that they are actually writing for. These physical and virtual networks grow, building their personal learning networks as they connect to more people who are connected to more people. (Steve’s a huge fan of Twitter. I’m not quite as connected as he is but that’s like saying this puddle is smaller than the North Sea.)
Some of our students are strongly connected and they do store their knowledge in groups and friendships, which really reflects how they find things out. This rolls into digital cultural capital and who our groups are.
(Then there was a steam of images at too high a speed for me to capture – go and download the slides, they’re creative commons and a lot of fun.)
Learners will need new competencies and literacies.
Always nice to hear Steve speak and, of course, I still agree with a lot of what he said. I won’t prod him for questions, though.
EduTech AU 2015, Day 2, Higher Ed Leaders, “Innovation + Technology = great change to higher education”, #edutechau
Posted: June 3, 2015 Filed under: Education | Tags: advocacy, collaboration, community, connectivity, design, education, educational problem, educational research, edutech2015, edutechau, ethics, grand challenge, higher education, learning, market forces, measurement, mit, mit media lab, Nicholas, nicholas negroponte, olpc, one laptop per child, principles of design, public education, resources, seymour papert, students, teaching, teaching approaches, thinking, tools Leave a commentBig session today. We’re starting with Nicholas Negroponte, founder of the MIT Media Lab and the founder of One Laptop Per Child (OLPC), an initiative to create/provide affordable educational devices for children in the developing world. (Nicholas is coming to us via video conference, hooray, 21st Century, so this may or not work well in translation to blogging. Please bear with me if it’s a little disjointed.)
Nicholas would rather be here but he’s bravely working through his first presentation of this type! It’s going to be a presentation with some radical ideas so he’s hoping for conversation and debate. The presentation is broken into five parts:
- Learning learning. (Teaching and learning as separate entities.)
- What normal market forces will not do. (No real surprise that standard market forces won’t work well here.)
- Education without curricula. (Learning comes from many places and situations. Understanding and establishing credibility.)
- Where do new ideas come from? (How do we get them, how do we not get in the way.)
- Connectivity as a human right. (Is connectivity a human right or a means to rights such as education and healthcare? Human rights are free so that raises a lot of issues.
Nicholas then drilled down in “Learning learning”, starting with a reference to Seymour Papert, and Nicholas reflected on the sadness of the serious accident of Seymour’s health from a personal perspective. Nicholas referred to Papert’s and Minsky’s work on trying to understand how children and machines learned respectively. In 1968, Seymour started thinking about it and on April, 9, 1970, he gave a talk on his thoughts. Seymour realised that thinking about programs gave insight into thinking, relating to the deconstruction and stepwise solution building (algorithmic thinking) that novice programmers, such as children, had to go through.
These points were up on the screen as Nicholas spoke:
- Construction versus instruction
- Why reinventing the wheel is good
- Coding as thinking about thinking
How do we write code? Write it, see if it works, see which behaviours we have that aren’t considered working, change the code (in an informed way, with any luck) and try again. (It’s a little more complicated than that but that’s the core.) We’re now into the area of transferable skills – it appeared that children writing computer programs learned a skill that transferred over into their ability to spell, potentially from the methodical application of debugging techniques.
Nicholas talked about a spelling bee system where you would focus on the 8 out of 10 you got right and ignore the 2 you didn’t get. The ‘debugging’ kids would talk about the ones that they didn’t get right because they were analsysing their mistakes, as a peer group and as individual reflection.
Nicholas then moved on to the failure of market forces. Why does Finland do so well when they don’t have tests, homework and the shortest number of school hours per day and school days per year. One reason? No competition between children. No movement of core resources into the private sector (education as poorly functioning profit machine). Nicholas identified the core difference between the mission and the market, which beautifully summarises my thinking.
The OLPC program started in Cambodia for a variety of reasons, including someone associated with the lab being a friend of the King. OLPC laptops could go into areas where the government wasn’t providing schools for safety reasons, as it needed minesweepers and the like. Nicholas’ son came to Cambodia from Italy to connect up the school to the Internet. What would the normal market not do? Telecoms would come and get cheaper. Power would come and get cheaper. Laptops? Hmm. The software companies were pushing the hardware companies, so they were both caught in a spiral of increasing power consumption for utility. Where was the point where we could build a simple laptop, as a mission of learning, that could have a smaller energy footprint and bring laptops and connectivity to billions of people.
This is one of the reasons why OLPC is a non-profit – you don’t have to sell laptops to support the system, you’re supporting a mission. You didn’t need to sell or push to justify staying in a market, as the production volume was already at a good price. Why did this work well? You can make partnerships that weren’t possible otherwise. It derails the “ah, you need food and shelter first” argument because you can change the “why do we need a laptop” argument to “why do we need education?” at which point education leads to increased societal conditions. Why laptops? Tablets are more consumer-focused than construction-focused. (Certainly true of how I use my tech.)
(When we launched the first of the Digital Technologies MOOCs, the deal we agreed upon with Google was that it wasn’t a profit-making venture at all. It never will be. Neither we nor Google make money from the support of teachers across Australia so we can have all of the same advantages as they mention above: open partnerships, no profit motive, working for the common good as a mission of learning and collegial respect. Highly recommended approach, if someone is paying you enough to make your rent and eat. The secret truth of academia is that they give you money to keep you housed, clothed and fed while you think. )
Nicholas told a story of kids changing from being scared or bored of school to using an approach that brings kids flocking in. A great measure of success.
Now, onto Education without curricula, starting by talking public versus private. This is a sensitive subject for many people. The biggest problem for public education in many cases is the private educational system, dragging out caring educators to a closed system. Remember Finland? There are no public schools and their educational system is astoundingly good. Nicholas’ points were:
- Public versus private
- Age segregation
- Stop testing. (Yay!)
The public sector is losing the imperative of the civic responsibility for education. Nicholas thinks it doesn’t make sense that we still segregate by ages as a hard limit. He thinks we should get away from breaking it into age groups, as it doesn’t clearly reflect where students are at.
Oh, testing. Nicholas correctly labelled the parental complicity in the production of the testing pressure cooker. “You have to get good grades if you’re going to Princeton!” The testing mania is dominating institutions and we do a lot of testing to measure and rank children, rather than determining competency. Oh, so much here. Testing leads to destructive behaviour.
So where do new ideas come from? (A more positive note.) Nicholas is interested in Higher Ed as sources of new ideas. Why does HE exist, especially if we can do things remotely or off campus? What is the role of the Uni in the future? Ha! Apparently, when Nicholas started the MIT media lab, he was accused of starting a sissy lab with artists and soft science… oh dear, that’s about as wrong as someone can get. His use of creatives was seen as soft when, of course, using creative users addressed two issues to drive new ideas: a creative approach to thinking and consulting with the people who used the technology. Who really invented photography? Photographers. Three points from this section.
- Children: our most precious natural resource
- Incrementalism is the enemy of creativity
- Brain drain
On the brain drain, we lose many, many students to other places. Uni are a place to solve huge problems rather than small, profit-oriented problems. The entrepreneurial focus leads to small problem solution, which is sucking a lot of big thinking out of the system. The app model is leading to a human resource deficit because the start-up phenomenon is ripping away some of our best problem solvers.
Finally, to connectivity as a human right. This is something that Nicholas is very, very passionate about. Not content. Not laptops. Being connected. Learning, education, and access to these, from early in life to the end of life – connectivity is the end of isolation. Isolation comes in many forms and can be physical, geographical and social. Here are Nicholas’ points:
- The end of isolation.
- Nationalism is a disease (oh, so much yes.) Nations are the wrong taxonomy for the world.
- Fried eggs and omelettes.
Fried eggs and omelettes? In general, the world had crisp boundaries, yolk versus white. At work/at home. At school/not at school. We are moving to a more blended, less dichotomous approach because we are mixing our lives together. This is both bad (you’re getting work in my homelife) and good (I’m getting learning in my day).
Can we drop kids into a reading environment and hope that they’ll learn to read? Reading is only 3,500 years old, versus our language skills, so it has to be learned. But do we have to do it the way that we did it? Hmm. Interesting questions. This is where the tablets were dropped into illiterate villages without any support. (Does this require a seed autodidact in the group? There’s a lot to unpack it.) Nicholas says he made a huge mistake in naming the village in Ethiopia which has corrupted the experiment but at least the kids are getting to give press conferences!
Another massive amount of interesting information – sadly, no question time!
EduTech Australia 2015, Day 1, Session 1, Higher Education Leaders @jselingo #edutechau
Posted: June 2, 2015 Filed under: Education, Opinion | Tags: advocacy, blogging, education, educational research, edutech2015, edutechau, higher education, Jeffrey Selingo, learning, students, teaching, teaching approaches, thinking, tools, workload Leave a commentEmeritus Professor Steven Schwartz, AM, opened the Higher Ed leaders session, following a very punchy video on how digital is doing “zoom” and “rock and roll” things. (I’m a bit jaded about “tech wow” videos but this one was pretty good. It reinforced the fact that over 60% of all web browsing is carried out on mobile devices, which should be a nudge to all of us designing for the web.)
There will be roughly 5,000 participants in the totally monstrous Brisbane Convention Centre. There are many people here that I know but I’m beginning to doubt whether I’m going to see many of them unless they’re speaking – there’s a mass of educational humanity here, people!
The opening talk was “The Universities of tomorrow, the future of anytime and anywhere learning”, presented by Jeffrey Selingo. Jeff writes books, “College Unbound” among others, and is regular contributor to the Washington Post and the Chronicle. (I live for the day I can put “Education Visionary” on my slides with even a shred of this credibility. As a note, remarks in parentheses are probably my editorial comments.)
(I’ve linked to Jeff on Twitter. Please correct me on anything, Jeff!)
Jeff sought out to explore the future of higher learning, taking time out from editing the Chronicle. He wanted to tell the story of higher ed for the coming decade, for those parents and students heading towards it now, rather than being in it now. Jeff approached it as a report, rather than an academic paper, and is very open about the fact that he’s not conducting research. “In journalism, if you have three anecdotes, you have a trend.”
(I’m tempted to claim phenomenography but I know you’ll howl me down. And rightly so!)
Higher Ed is something that, now, you encounter once in our lives and then move on. But the growth in knowledge and ongoing explosion of new information doesn’t match that model. Our Higher Ed model is based on an older tradition and and older informational model.
(This is great news for me, I’m a strong advocate of an integrated and lifelong Higher Ed experience)
(Slides for this talk available at http://jeffselingo.com/conference
Be warned, you have to sign up for a newsletter to get the slides.)
Jeff then talked about his start, in one of the initial US college rankings, before we all ranked each other into the ground. The ‘prestige race’ as he refers to it. Every university around the world wanted to move up the ladder. (Except for the ones on the top, kicking at the rungs below, no doubt.)
“Prestige is to higher education as profit is to corporations.”
According to Caroline Hoxby, Higher Ed student flow has increased as students move around the world. Students who can move to different Universities, now tend to do so and they can exercise choices around the world. This leads to predictions like “the bottom 25% of Unis will go out of business or merge” (Clay Christensen) – Jeff disagrees with this although he thinks change is inevitable.
We have a model of new, technologically innovative and agile companies destroy the old leaders. Netflix ate Blockbuster. Amazon ate Borders. Apple ate… well, everybody… but let’s say Tower Records, shall we? Jeff noted that journalism’s upheaval has been phenomenal, despite the view of journalism as a ‘public trust’. People didn’t want to believe what was going to happen to their industry.
Jeff believes that students are going to drive the change. He believes that students are often labelled as “Traditional” (ex-school, 18-22, direct entry) and “non-Traditional” (adult learners, didn’t enter directly.) But what this doesn’t capture is the mindset or motivation of students to go to college. (MOOC motivation issues, anyone?)
What do students want to get out of their degree?
(Don’t ask difficult questions like that, Jeff! It is, of course, a great question and one we try to ask but I’m not sure we always listen.)
Why are you going? What do you want? What do you want your degree to look like? Jeff asked and got six ‘buckets’ of students in two groups, split across the trad/non-trad age groups.
Group 1 are the younger group and they break down into.
- Young Academics (24%) – the trad high-performing students who have mastered the earlier education systems and usually have a privileged background
- Coming of Age (11%) – Don’t quite know what they want from Uni but they were going to college because it was the place to go to become an adult. This is getting them ready to go to the next step, the work force.
- Career Starters (18%) – Students who see the Uni as a means to the end, credentialing for the job that they want. Get through Uni as quickly as possible.
Group 2 are older:
- Career Accelerators (21%) – Older students who are looking to get new credentials to advance themselves in their current field.
- Industry Switchers – Credential changers to move to a new industry.
- Adult Wanderers – needed a degree because that was what the market told them but they weren’t sure why
(Apologies for losing some of the stats, the room’s quite full and some people had to walk past me.)
But that’s what students are doing – what skills are required out there from the employers?
- Written and Oral communication
- Managing multiple priorities
- Collaboration
- Problem solving
People used to go to college for a broad knowledge base and then have that honed by an employer or graduate school to focus them into a discipline. Now, both of these are expected at the Undergrad level, which is fascinating given that we don’t have extra years to add to the degree. But we’re not preparing students better to enter college, nor do we have the space for experiential learning.
Expectations are greater than ever but are we delivering?
When do we need higher education? Well, it used to be “education” then “employment” then “retirement”. The new model, today, (from Georgetown, Tony Carnevale), we have “education”, then “learning and earning”, then “full-time work and on-the-job training”, “transition to retirement” and, finally, “full retirement”. Students are finally focusing on their career at around 30, after leaving the previous learning phases. This is, Jeff believes, where we are not playing an important role for students in their 20s, which is not helping them in their failure to launch.
Jeff was wondering how different life would be for the future, especially given how much longer we are going to be living. How does that Uni experience of “once in our lives, in one physical place” fit in, if people may switch jobs much more frequently over a longer life? The average person apparently switches jobs every four years – no wonder most of the software systems I use are so bad!
Je”s “College Unbound” future is student-driven, student-centred, and not a box that is entered at 18 and existed 4 years later, it’s a platform for life-long learning.
“The illiterate will be those who cannot learn, unlearn and relearn” – Alvin Toffler
Jeff doesn’t think that there will be one simple path to the future. Our single playing field competition of institutions has made us highly similar in the higher ed sector. How can we personalise pathways to the different groups of students that we saw above? Predictive analytics are important here – technology is vital. Good future education will be adaptive and experiential, combining the trad classroom with online systems. apprenticeships and, overall, removing the requirement to reside at or near your college.
Jeff talked about some new models, starting with the Swirl, the unbundled degree across different institutions, traditional snd not. Multiple universities, multiple experiences = degree.
Then there’s mixing course types, mixing face-to-face with hybrid and online to accelerate their speed of graduation. (There is a strong philosophical point on this that I hope to get back to later: why are we racing through University?)
Finally, competency-based learning allowed a learner to have class lengths from 2 weeks to 14 weeks, based on what she already knew. (I am a really serious advocate of this approach. I advocated to switch our entire first year for Engineering to a competency based approach but I’ll write more about that later on. And, no, we didn’t do it but at least we thought about it.)
In the mix are smaller chunks of information and just-in-time learning. Anyone who has used YouTube for a Photoshop tutorial has had a positive (well, as positive as it can be) experience with this. Why can’t we do this with any number of higher ed courses?
A note on the Stanford 2025 Design School exercise: the open loop education. Accepted to Stanford would give you access to 6 years of education that you would be able to use at any point in your life. Take two years, go out and work a bit, come back. Why isn’t the University at the centre of our lifelong involvement with learning?
The distance between producer and consumer is shrinking, whether it’s online stores or 3-D printing. Example given was MarginalRevolutionUniversity, a homegrown University, developed by a former George Mason academic.
As aways, the MOOC dropout rate was raised. Yes, only 10% complete, but Jeff’s interviews confirm what we already know, most of those students had no intention of completing. They didn’t think of the MOOC course as a course or as part of a degree, they were dipping in to get what they needed, when they needed it. Just like those YouTube Photoshop tutorials.
The difficult question is how certify this. And… here are badges again, part of certification of learning and the challenge is how we use them.
Jeff think that there are still benefits for residential experience, although assisted and augmented with technology:
- Faculty mentoring
- Undergraduate research (team work, open problems)
- Be creative. Take Risks. Learn how to fail.
- Cross-cultural experience.
Of course, not all of this is available to everyone. And what is the return on investment for this? LinkedIn finally has enough data that we can start to answer that question. (People will tell LinkedIn things that they won’t tell other people, apparently.) This may change the ranking game because rankings can now be conducted on outputs rather than inputs. Watch this space?
The world is changing. What does Jeff think? Ranking is going to change and we need to be able to prove our value. We have to move beyond isolated disciplines. Skill certification is going to get harder but the overall result should be better. University is for life, not just for three years. This will require us to build deep academic alliances that go beyond our traditional boxes.
Ok, prepping for the next talk!
What to support? Thoughts on funding for ideas. We must fund the forges of creativity as well as the engines of science (@JulianBurnside #ideasforaus)
Posted: May 3, 2015 Filed under: Education, Opinion | Tags: advocacy, authenticity, biological science, community, education, educational research, ethics, higher education, Julian Burnside AO QC, Mr Burnside, Opera House, principles of design, reflection, resources Leave a commentThe barrister and #HumanRightsExtremist, Julian Burnside AO QC, was part of today’s Carnegie Conversations at the Opera House. While I’m not there, I was intrigued by a tweet he sent about other discussions going on today regarding the investment of our resources to do the maximum good. (I believe that this was the session following his, with Peter Singer and chaired by Ann Cherry.)
Mr Burnside’s Tweet was (for those who haven’t seen the image):
What to support? Effective Altruism is good, but what about funding the arts, ideas and other things which can’t be measured? #ideasforaus
Some of the responses to this Tweet tried to directly measure the benefits of a cure for Malaria against funding the arts and, to me, this misses the point. I am a scientist, an artist, a husband, a cat steward, and many other things. As a scientist, I use the scientific method when I am undertaking my research into improving education for students and developing better solutions for use of technology. If you were to ask me which is better, putting funds into distributing a malarial cure or subsiding an opera, then we are so close to the endpoint of the activity that the net benefit can be measured. But if you were to ask me whether this means we could defund the arts to concentrate on biological science, I’d have to say no, because the creative development of solutions is not strictly linked to the methodical application of science.
As a computer scientist, I work in vast artificial universes where it is impossible to explore every option because we do not have enough universe. I depend upon insights and creativity to help me work out the solutions, which I can then test methodically. This is a known problem in all forms of large-scale optimisation – we have to settle for finding what we can, seeking the best, and we often have to step away to make sure that the peak we have ascended is not a foothill in the shadow of a greater mountain.
Measuring what goes into the production of a new idea is impossible. I can tell you that a number of my best solutions have come from weeks or months of thinking, combined with music, visits to art galleries, working with my hands, the pattern of water in the shower and the smell of fresh bread.
Once we have an idea then, yes, absolutely, let us fund centres and institutions that support and encourage the most rigorous and excellent mechanisms for turning ideas into reality. When we have a cure for malaria, we must fund it and distribute it, working on ways to reduce delays and cost mark-ups to those who need it most. But we work in spaces so big that walking the whole area is impossible. We depend upon leaps of intuition, creative exploration of solution spaces and, on occasion, flashes of madness to find the ideas that we can then develop
To think that we can focus only on the measurable outcomes is to totally miss the fact that we have no real idea where many of our best ideas come from and yet so many of us have stories of insight and clarity that stem from our interactions with a rich, developed culture of creativity. And that means funding the arts, the ideas and things that we cannot measure.
(Edited to make the hashtag at the top less likely to be misparsed.)
Think. Create. Code. Vis! (@edXOnline, @UniofAdelaide, @cserAdelaide, @code101x, #code101x)
Posted: April 30, 2015 Filed under: Education, Opinion | Tags: #code101x, advocacy, blogging, collaboration, community, curriculum, data visualisation, education, educational problem, educational research, edx, higher education, learning, measurement, MOOC, moocs, reflection, resources, teaching, teaching approaches, thinking, tools, universal principles of design Leave a commentI just posted about the massive growth in our new on-line introductory programming course but let’s look at the numbers so we can work out what’s going on and, maybe, what led to that level of success. (Spoilers: central support from EdX helped a huge amount.) So let’s get to the data!
I love visualised data so let’s look at the growth in enrolments over time – this is really simple graphical stuff as we’re spending time getting ready for the course at the moment! We’ve had great support from the EdX team through mail-outs and Twitter and you can see these in the ‘jumps’ in the data that occurred at the beginning, halfway through April and again at the end. Or can you?
Hmm, this is a large number, so it’s not all that easy to see the detail at the end. Let’s zoom in and change the layout of the data over to steps so we can things more easily. (It’s worth noting that I’m using the free R statistical package to do all of this. I can change one line in my R program and regenerate all of my graphs and check my analysis. When you can program, you can really save time on things like this by using tools like R.)

Now you can see where that increase started and then the big jump around the time that e-mail advertising started, circled. That large spike at the end is around 1500 students, which means that we jumped 10% in a day.
When we started looking at this data, we wanted to get a feeling for how many students we might get. This is another common use of analysis – trying to work out what is going to happen based on what has already happened.
As a quick overview, we tried to predict the future based on three different assumptions:
- that the growth from day to day would be roughly the same, which is assuming linear growth.
- that the growth would increase more quickly, with the amount of increase doubling every day (this isn’t the same as the total number of students doubling every day).
- that the growth would increase even more quickly than that, although not as quickly as if the number of students were doubling every day.
If Assumption 1 was correct, then we would expect the graph to look like a straight line, rising diagonally. It’s not. (As it is, this model predicted that we would only get 11,780 students. We crossed that line about 2 weeks ago.
So we know that our model must take into account the faster growth, but those leaps in the data are changes that caused by things outside of our control – EdX sending out a mail message appears to cause a jump that’s roughly 800-1,600 students, and it persists for a couple of days.
Let’s look at what the models predicted. Assumption 2 predicted a final student number around 15,680. Uhh. No. Assumption 3 predicted a final student number around 17,000, with an upper bound of 17,730.
Hmm. Interesting. We’ve just hit 17,571 so it looks like all of our measures need to take into account the “EdX” boost. But, as estimates go, Assumption 3 gave us a workable ballpark and we’ll probably use it again for the next time that we do this.
Now let’s look at demographic data. We now we have 171-172 countries (it varies a little) but how are we going for participation across gender, age and degree status? Giving this information to EdX is totally voluntary but, as long as we take that into account, we make some interesting discoveries.
Our median student age is 25, with roughly 40% under 25 and roughly 40% from 26 to 40. That means roughly 20% are 41 or over. (It’s not surprising that the graph sits to one side like that. If the left tail was the same size as the right tail, we’d be dealing with people who were -50.)
The gender data is a bit harder to display because we have four categories: male, female, other and not saying. In terms of female representation, we have 34% of students who have defined their gender as female. If we look at the declared male numbers, we see that 58% of students have declared themselves to be male. Taking into account all categories, this means that our female participant percentage could be as high as 40% but is at least 34%. That’s much higher than usual participation rates in face-to-face Computer Science and is really good news in terms of getting programming knowledge out there.
We’re currently analysing our growth by all of these groupings to work out which approach is the best for which group. Do people prefer Twitter, mail-out, community linkage or what when it comes to getting them into the course.
Anyway, lots more to think about and many more posts to come. But we’re on and going. Come and join us!
Think. Create. Code. Wow! (@edXOnline, @UniofAdelaide, @cserAdelaide, @code101x, #code101x)
Posted: April 30, 2015 Filed under: Education, Opinion | Tags: #code101x, advocacy, authenticity, blogging, community, cser digital technologies, curriculum, digital technologies, education, educational problem, educational research, ethics, higher education, Hugh Davis, learning, MOOC, moocs, on-line learning, research, Southampton, student perspective, teaching, teaching approaches, thinking, tools, University of Southampton 1 CommentThings are really exciting here because, after the success of our F-6 on-line course to support teachers for digital technologies, the Computer Science Education Research group are launching their first massive open on-line course (MOOC) through AdelaideX, the partnership between the University of Adelaide and EdX. (We’re also about to launch our new 7-8 course for teachers – watch this space!)
Our EdX course is called “Think. Create. Code.” and it’s open right now for Week 0, although the first week of real content doesn’t go live until the 30th. If you’re not already connected with us, you can also follow us on Facebook (code101x) or Twitter (@code101x), or search for the hashtag #code101x. (Yes, we like to be consistent.)
I am slightly stunned to report that, less than 24 hours before the first content starts to roll out, that we have 17,531 students enrolled, across 172 countries. Not only that, but when we look at gender breakdown, we have somewhere between 34-42% women (not everyone chooses to declare a gender). For an area that struggles with female participation, this is great news.
I’ll save the visualisation data for another post, so let’s quickly talk about the MOOC itself. We’re taking a 6 week approach, where students focus on developing artwork and animation using the Processing language, but it requires no prior knowledge and runs inside a browser. The interface that has been developed by the local Adelaide team (thank you for all of your hard work!) is outstanding and it’s really easy to make things happen.
I love this! One of the biggest obstacles to coding is having to wait until you see what happens and this can lead to frustration and bad habits. In Processing you can have a circle on the screen in a matter of seconds and you can start playing with colour in the next second. There’s a lot going on behind the screen to make it this easy but the student doesn’t need to know it and can get down to learning. Excellent!
I went to a great talk at CSEDU last year, presented by Hugh Davis from Southampton, where Hugh raised some great issues about how MOOCs compared to traditional approaches. I’m pleased to say that our demography is far more widespread than what was reported there. Although the US dominates, we have large representations from India, Asia, Europe and South America, with a lot of interest from Africa. We do have a lot of students with prior degrees but we also have a lot of students who are at school or who aren’t at University yet. It looks like the demography of our programming course is much closer to the democratic promise of free on-line education but we’ll have to see how that all translates into participation and future study.
While this is an amazing start, the whole team is thinking of this as part of a project that will be going on for years, if not decades.
When it came to our teaching approach, we spent a lot of time talking (and learning from other people and our previous attempts) about the pedagogy of this course: what was our methodology going to be, how would we implement this and how would we make it the best fit for this approach? Hugh raised questions about the requirement for pedagogical innovation and we think we’ve addressed this here through careful customisation and construction (we are working within a well-defined platform so that has a great deal of influence and assistance).
We’ve already got support roles allocated to staff and students will see us on the course, in the forums, and helping out. One of the reasons that we tried to look into the future for student numbers was to work out how we would support students at this scale!
One of our most important things to remember is that completion may not mean anything in the on-line format. Someone comes on and gets an answer to the most pressing question that is holding them back from coding, but in the first week? That’s great. That’s success! How we measure that, and turn that into traditional numbers that match what we do in face-to-face, is going to be something we deal with as we get more information.
The whole team is raring to go and the launch point is so close. We’re looking forward to working with thousands of students, all over the world, for the next six weeks.
Sound interesting? Come and join us!
Musing on Industrial Time
Posted: April 20, 2015 Filed under: Education, Opinion | Tags: advocacy, authenticity, blogging, community, curriculum, design, education, educational problem, educational research, ethics, higher education, in the student's head, learning, measurement, principles of design, reflection, resources, student perspective, teaching, teaching approaches, thinking, time banking, universal principles of design, work/life balance, workload 3 CommentsI caught up with a good friend recently and we were discussing the nature of time. She had stepped back from her job and was now spending a lot of her time with her new-born son. I have gone to working three days a week, hence have also stepped back from the five-day grind. It was interesting to talk about how this change to our routines had changed the way that we thought of and used time. She used a term that I wanted to discuss here, which was industrial time, to describe the clock-watching time of the full-time worker. This is part of the larger area of time discipline, how our society reacts to and uses time, and is really quite interesting. Both of us had stopped worrying about the flow of time in measurable hours on certain days and we just did things until we ran out of day. This is a very different activity from the usual “do X now, do Y in 15 minutes time” that often consumes us. In my case, it took me about three months of considered thought and re-training to break the time discipline habits of thirty years. In her case, she has a small child to help her to refocus her time sense on the now.
Modern time-sense is so pervasive that we often don’t think about some of the underpinnings of our society. It is easy to understand why we have years and, although they don’t line up properly, months given that these can be matched to astronomical phenomena that have an effect on our world (seasons and tides, length of day and moonlight, to list a few). Days are simple because that’s one light/dark cycle. But why there are 52 weeks in a year? Why are there 7 days in a week? Why did the 5-day week emerge as a contiguous block of 5 days? What is so special about working 9am to 5pm?
A lot of modern time descends from the struggle of radicals and unionists to protect workers from the excesses of labour, to stop people being worked to death, and the notion of the 8 hour day is an understandable division of a 24 hour day into three even chunks for work, rest and leisure. (Goodness, I sound like I’m trying to sell you chocolate!)
If we start to look, it turns out that the 7 day week is there because it’s there, based on religion and tradition. Interestingly enough, there have been experiments with other week lengths but it appears hard to shift people who are used to a certain routine and, tellingly, making people wait longer for days off appears to be detrimental to adoption.
If we look at seasons and agriculture, then there is a time to sow, to grow, to harvest and to clear, much as there is a time for livestock to breed and to be raised for purpose. If we look to the changing time of sunrise and sunset, there is a time at which natural light is available and when it is not. But, from a time discipline perspective, these time systems are not enough to be able to build a large-scale, industrial and synchronised society upon – we must replace a distributed, loose and collective notion of what time is with one that is centralised, authoritarian and singular. While religious ceremonies linked to seasonal and astronomical events did provide time-keeping on a large scale prior to the industrial revolution, the requirement for precise time, of an accuracy to hours and minutes, was not possible and, generally, not required beyond those cues given from nature such as dawn, noon, dusk and so on.
After the industrial revolution, industries and work was further developed that was heavily separated from a natural linkage – there are no seasons for a coal mine or a steam engine – and the development of the clock and reinforcement of the calendar of work allowed both the measurement of working hours (for payment) and the determination of deadlines, given that natural forces did not have to be considered to the same degree. Steam engines are completed, they have no need to ripen.
With the notion of fixed and named hours, we can very easily determine if someone is late when we have enough tools for measuring the flow of time. But this is, very much, the notion of the time that we use in order to determine when a task must be completed, rather than taking an approach that accepts that the task will be completed at some point within a more general span of time.
We still have confusion where our understanding of “real measures” such as days, interact with time discipline. Is midnight on the 3rd of April the second after the last moment of April the 2nd or the second before the first moment of April the 4th? Is midnight 12:00pm or 12:00am? (There are well-defined answers to this but the nature of the intersection is such that definitions have to be made.)
But let’s look at teaching for a moment. One of the great criticisms of educational assessment is that we confuse timeliness, and in this case we specifically mean an adherence to meeting time discipline deadlines, with achievement. Completing the work a crucial hour after it is due can lead to that work potentially not being marked at all, or being rejected. But we do usually have over-riding reasons for doing this but, sadly, these reasons are as artificial as the deadlines we impose. Why is an Engineering Degree a four-year degree? If we changed it to six would we get better engineers? If we switched to competency based training, modular learning and life-long learning, would we get more people who were qualified or experienced with engineering? Would we get less? What would happen if we switched to a 3/1/2/1 working week? Would things be better or worse? It’s hard to evaluate because the week, and the contiguous working week, are so much a part of our world that I imagine that today is the first day that some of you have thought about it.
Back to education and, right now, we count time for our students because we have to work out bills and close off accounts at end of financial year, which means we have to meet marking and award deadlines, then we have to project our budget, which is yearly, and fit that into accredited degree structures, which have year guidelines…
But I cannot give you a sound, scientific justification for any of what I just wrote. We do all of that because we are caught up in industrial time first and we convince ourselves that building things into that makes sense. Students do have ebb and flow. Students are happier on certain days than others. Transition issues on entry to University are another indicator that students develop and mature at different rates – why are we still applying industrial time from top to bottom when everything we see here says that it’s going to cause issues?
Oh, yes, the “real world” uses it. Except that regular studies of industrial practice show that 40 hour weeks, regular days off, working from home and so on are more productive than the burn-out, everything-late, rush that we consider to be the signs of drive. (If Henry Ford thinks that making people work more than 40 hours a week is bad for business, he’s worth listening to.) And that’s before we factor in the development of machines that will replace vast numbers of human jobs in the next 20 years.
I have a different approach. Why aren’t we looking at students more like we regard our grape vines? We plan, we nurture, we develop, we test, we slowly build them to the point where they can produce great things and then we sustain them for a fruitful and long life. When you plant grape vines, you expect a first reasonable crop level in three years, and commercial levels at five. Tellingly, the investment pattern for grapes is that it takes you 10 years to break even and then you start making money back. I can’t tell you how some of my students will turn out until 15-25 years down the track and it’s insanity to think you can base retrospective funding on that timeframe.
You can’t make your grapes better by telling them to be fruitful in two years. Some vines take longer than others. You can’t even tell them when to fruit (although can trick them a little). Yet, somehow, we’ve managed to work around this to produce a local wine industry worth around $5 billion dollars. We can work with variation and seasonal issues.
One of the reasons I’m so keen on MOOCs is that these can fit in with the routines of people who can’t dedicate themselves to full-time study at the moment. By placing well-presented, pedagogically-sound materials on-line, we break through the tyranny of the 9-5, 5 day work week and let people study when they are ready to, where they are ready to, for as long as they’re ready to. Like to watch lectures at 1am, hanging upside down? Go for it – as long as you’re learning and not just running the video in the background while you do crunches, of course!
Once you start to question why we have so many days in a week, you quickly start to wonder why we get so caught up on something so artificial. The simple answer is that, much like money, we have it because we have it. Perhaps it’s time to look at our educational system to see if we can do something that would be better suited to developing really good knowledge in our students, instead of making them adept at sliding work under our noses a second before it’s due. We are developing systems and technologies that can allow us to step outside of these structures and this is, I believe, going to be better for everyone in the process.
Conformity isn’t knowledge, and conformity to time just because we’ve always done that is something we should really stop and have a look at.
The Sad Story of Dr Karl Kruszelnicki
Posted: April 16, 2015 Filed under: Education, Opinion | Tags: advocacy, authenticity, blogging, Dr Karl, education, educational problem, ethics, feedback, higher education, Karl Kruszelnicki, reflection, teaching, teaching approaches, thinking Leave a commentDr Karl is a very familiar face and voice in Australia, for his role in communicating and demystifying science. He’s a polymath and skeptic, with a large number of degrees and a strong commitment to raising awareness on crucial issues such as climate change and puncturing misconceptions and myths. With 33 books and an extensive publishing career, it’s no surprise that he’s a widely respected figure in the area of scientific communication and he holds a fellowship at the University of Sydney on the strength of his demonstrated track record and commitment to science.
It is a very sad state of events that has led to this post, where we have to talk about how his decision to get involved in a government-supported advertising campaign has had some highly undesirable outcomes. The current government of Australia has had, being kind, a questionable commitment to science, not appointing a science minister for the first time in decades, undermining national initiatives in alternative and efficient energy, and having a great deal of resistance to issues such as the scientific consensus on climate change. However, as part of the responsibilities of government, the Intergenerational Report is produced at least every 5 years (this one was a wee bit late) and has the tricky job of crystal-balling the next 40 years to predict change and allow government policy to be shaped to handle that change. Having produced the report, the government looked for a respected science-focused speaker to front the advertising campaign and they recruited Dr Karl, who has recently been on the TV talking about some of the things in the report as part of a concerted effort to raise awareness of the report.
But there’s a problem.
And it’s a terrible problem because it means that Dr Karl didn’t follow some of the most basic requirements of science. From an ABC article on this:
“Dr Kruszelnicki said he was only able to read parts of the report (emphasis mine) before he agreed to the ads as the rest was under embargo.”
Ah. But that’s ok, if he agrees with the report as it’s been released, right? Uhh. About that, from a Fairfax piece on Tuesday.
“The man appearing on television screens across the country promoting the Abbott government’s Intergenerational Report – science broadcaster Karl Kruszelnicki – has hardened his stance against the document, describing it as “flawed” and admitting to concerns that it was “fiddled with” by the government.” (emphasis mine, again)
Dr Karl now has concerns over the independence of the report (he now sees it as a primarily political document) and much of its content. Ok, now we have a problem. He’s become the public face of a report that he didn’t read and that he took, very naïvely, on faith that the parts he hadn’t seen would (somewhat miraculously) reverse the well-known direction of the current government on climate change. But it’s not as if he just took money to front something he didn’t read, is it? Oh. He hasn’t been paid for it yet but this was a paid gig. Obviously, the first thing to do is to not take the money, if you’re unhappy with the report, right? Urm. From the SMH link above:
“What have I done wrong?” he told Fairfax Media. “As far as I’m concerned I was hired to bring the public’s attention to the report. People have heard about this one where they hadn’t heard about IGR one, two or three.”
But then public reaction on Twitter and social media started to rise and, last night, this was released on his Twitter account:
“I have decided to donate any moneys received from the IGR campaign to needy government schools. More to follow tomorrow. Dr Karl.”
This is a really sad day for science communication in Australia. As far as I know, the campaign is still running and, while you can easily find the criticism of the report if you go looking for it, a number of highly visible media sites are not showing anything that would lead readers to think that anyone had any issues with the report. So, while Dr Karl is regretting his involvement, it continues to persuade people around Australia that this friendly, trusted and respected face of science communication is associated with the report. Giving the money away (finally) to needy schools does not fix this. But let me answer Dr Karl’s question from above, “What have I done wrong?” With the deepest regret, I can tell you that what you have done wrong is:
- You presented a report with your endorsement without reading it,
- You arranged to get paid to do this,
- You consumed the goodwill and trust of the identity that you have formed over decades of positive scientific support to do this,
- You assisted the on-going anti-scientific endeavours of a government that has a bad track record in this area, and
- You did not immediately realise that what you had done was a complete failure of the implicit compact that you had established with the Australian public as a trusted voice of rationality, skepticism and science.
We all make mistakes and scientists do it all the time, on outdated, inaccurate, misreported and compromised data. But the moment we know that the data is wrong, we have to find the truth and come up with new approaches. But it is a serious breach of professional scientific ethics to present something where you cannot vouch for it through established soundness of reputation (a ‘good’ journal), trusted reference (an established scientific expert) or personal investigation (your own research). And that’s purely in papers or at conferences, where you are looking at relatively small issue of personal reputation or paper citations. To stand up on the national stage, for money, and to effectively say “This is Dr Karl approved”, when you have not read it, and then to hide behind an “but I was only presenting it” defence initially is to take an error of judgement and compound it into an offence that would potentially strip some scientists of their PhDs.
It’s great that Dr Karl is now giving the money away but the use of his image, with his complicity, has done its damage. There are people around Australia who will think that a report that is heavily politicised and has a great deal of questionable science in it is now scientific because Dr Karl stood there. We can’t undo that easily.
I don’t know what happens now. Dr Karl is a broadcaster but he does have a University appointment. I’ll be interested to see if his own University convenes an ethics and professional practice case against him. Maybe it will fade away, in time. Dr Karl has done so much for science in Australia that I hope that he has a good future after this but he has to come to terms with the fact that he has made the most serious error a scientist can make and I think he has a great deal of thinking to do as to what he wants to do next. Taking money from a till and then giving it back when you get caught doesn’t change the fact of what you did to get it – neither does agreeing to take cash to shill a report that you haven’t read.
But maybe I am being too harsh? The fellowship Dr Karl holds is named after Dr Julius Sumner Miller, a highly respected scientific communicator, who then used his high profile to sell chocolate in his final years (much to my Grandfather’s horror). Because nothing says scientific integrity like flogging chocolate for hard cash. Perhaps the fellowship has some sort of commercialising curse?
Actually, I don’t think I’m being too harsh, I wish him the best but I think he’s put himself into the most awful situation. I know what I would do but, then, I hope I would have seen that, just possibly, the least scientifically focused government in Australia might not be able to be trusted with an unseen report. If he had seen the report and then they had changed it all, that’s a scandal and he is a hero of scientific exposure. But that’s not the case. It’s a terribly sad day and a sad story for someone who, up until now, I had the highest respect for.







